IVA Performance Dashboard Interactive Budget Model
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Solution Overview
Problem
Current Intelligent Virtual Assistant (IVA) technologies lack an effective performance dashboard and interactive model to optimize IVA development across performance metrics, leading to inefficiencies in cost management and performance evaluation.
Innovation Solution
A graphical user interface with adjustable display elements representing key performance indicators (KPIs) that allow users to interact and model budget allocation across IVA development metrics, using aggregated historical data and regression analysis to correlate and visualize the impact of cost changes on IVA performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IVA development budget is increased to improve performance metrics, then IVA accuracy and efficiency are improved, but development cost increases
Solution Approach 1:
The system changes the parameters of IVA development by using regression analysis to model the relationships between budget allocation and performance metrics. The interactive dashboard allows users to adjust budget parameters and see predicted changes in accuracy, efficiency, and other KPIs, enabling data-driven parameter optimization without excessive cost increases.
Solution Approach 2:
The system implements feedback through the interactive dashboard that shows predicted performance metric changes based on budget allocation adjustments. Users can see how changes in one metric affect others, providing continuous feedback to optimize the balance between cost and performance.
2Reliability
If more resources are allocated to improve IVA performance metrics, then customer experience is improved, but support costs increase
Solution Approach 1:
The system optimizes the parameters of resource allocation by modeling the relationship between support costs and customer experience metrics. The regression analysis identifies the optimal parameter settings that maximize customer experience while minimizing support costs, showing where diminishing returns occur.
Solution Approach 2:
The interactive dashboard provides feedback on how resource allocation changes impact both customer experience and support costs, enabling decision-makers to see the tradeoffs in real-time and adjust allocations to achieve the optimal balance.
3Loss of time
If IVA development is accelerated to reduce deployment time, then market competitiveness is improved, but development quality may deteriorate
Solution Approach 1:
The system applies dynamics by creating a flexible, adjustable model that can simulate different development scenarios. Users can dynamically adjust deployment time parameters and see the predicted impact on development quality metrics, allowing them to find the optimal balance for their specific needs.
Solution Approach 2:
The regression analysis performs preliminary action by pre-calculating the relationships between development time, quality, and cost metrics based on historical data. This allows the system to predict outcomes before actual development decisions are made, enabling better planning to achieve both speed and quality.
Data Source
AI summary
Disclosed is a measure to collect and aggregate performance, sales, call center, custom KPI, and WA data in order to construct a model of correlations and causations between metrics to provide a means to measure associated costs of improving performance metrics for use in an interactive planning model. The interactive planning model allows for allocating budget across performance metrics, leveraging correlations and multiple cost models. The information is provided via a dashboard of IVA performance metrics and allows for comparison of real time IVA performance metrics to target metrics set by the IVA owner and incorporating KPIs provided by the WA owners.